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Evidential Combination Operators for Entrapment Prediction in Advanced Driver Assistance Systems
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Distributed Real-Time Systems)ORCID-id: 0000-0003-2973-3112
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))
Advanced Technology and Research, Volvo Group Trucks Technology, Gothenburg, Sweden.
2014 (engelsk)Inngår i: Foundations of Intelligent Systems: 21st International Symposium, ISMIS 2014, Roskilde, Denmark, June 25-27, 2014. Proceedings / [ed] Troels Andreasen; Henning Christiansen; Juan-Carlos Cubero; Zbigniew W. Raś, Springer International Publishing Switzerland , 2014, s. 194-203Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

We propose the use of evidential combination operators for advanced driver assistance systems (ADAS) for vehicles. More specifically, we elaborate on how three different operators, one precise and two imprecise, can be used for the purpose of entrapment prediction, i.e., to estimate when the relative positions and speeds of the surrounding vehicles can potentially become dangerous. We motivate the use of the imprecise operators by their ability to model uncertainty in the underlying sensor information and we provide an example that demonstrates the differences between the operators.

sted, utgiver, år, opplag, sider
Springer International Publishing Switzerland , 2014. s. 194-203
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 8502
Emneord [en]
Evidential combination operators, advanced driver assistance systems, Bayesian theory, credal sets, Dempster-Shafer theory
HSV kategori
Forskningsprogram
Teknik; Distribuerade realtidssystem (DRTS); Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
URN: urn:nbn:se:his:diva-9707DOI: 10.1007/978-3-319-08326-1_20Scopus ID: 2-s2.0-84903591422ISBN: 978-3-319-08325-4 (tryckt)ISBN: 978-3-319-08326-1 (digital)OAI: oai:DiVA.org:his-9707DiVA, id: diva2:736000
Konferanse
21st International Symposium, ISMIS 2014, Roskilde, Denmark, June 25-27, 2014
Forskningsfinansiär
Knowledge Foundation, 2010-0320
Merknad

Springer Cham

This work was supported by the Information Fusion Research Program (University of Skövde, Sweden), in partnership with the Swedish Knowledge Foundation under grant 2010-0320 (URL: http://www.infofusion.se, UMIF project).

Tilgjengelig fra: 2014-08-04 Laget: 2014-08-04 Sist oppdatert: 2023-03-24bibliografisk kontrollert

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